Papers by Author: Michael Hayes

Abstract: Return loss of wireless sensor network (WSN) node indicates the impedance matching between signal ports of the RF chip and the antenna, and thus shows the transmission efficiency in the signal path. All circuit components, including capacitors, inductors, PCB tracks, packaging parasitic and RF ports were modeled as equivalent passives, to achieve accurate simulation result of return loss of the WSN node. An optimization methodology of return loss was proposed based on the parameter sweep of the equivalent passive network simulation. With the help of the methodology, some critical components’ values were changed to obtain optimized RF performance for the wireless node. Measurements matched the analysis and simulation well and showed great improvement.

Abstract: Wireless sensor networks are frequently used to monitor temperature and other manufacturing parameters in recent years. However, the limited battery life posts a constraint for large sensor networks. In this work, thermoelectric energy harvester is designed to effectively convert the heat into electrical energy to power the wireless sensor node. Bismuth telluride thermoelectric modules are optimized for low temperature conditions. Charge pump and switching regulator based power management module is designed to efficiently step up the 500mV thermoelectric voltage to 3.0V level for wireless sensor nodes. This design employs electric double-layer capacitor based energy storage with considerations on practical wireless sensor node operation. The implemented energy harvester prototype is proposed for Tyndall wireless sensor system to monitor temperature and relative humidity in manufacturing process. The prototype was tested in various conditions to discover the issues in this practical design. The proposed prototype can expect a 15 years operative lifetime instead of the 3-6 months battery lifetime.

Abstract: In this paper, the effect of the substrate on wireless sensor network (WSN) node’s RF performance is studied experimentally by using different substrate materials with different thickness. A six-layer FR4 substrate PCB WSN node is fabricated and compared with the original two-layer FR4 PCB node to show the impact of substrate material thickness. Also different substrate dielectric constants’ impacts are studied by the same method. All these demonstrators are modeling by RF circuit analysis method and simulated in the Ansoft Designer software. Simulation results match the experimental measurement. An optimization method based on simulation for WSN node design with different substrate is presented. This analysis, modeling, simulation and optimization procedure can be carried out on some novel substrate materials such as LTCC and LCP.